1 Recherche des niveaux d’expression des gènes cibles embryonnaires (Menoret et al. 2013) dans le RNAseq des S2

library(drc)
library(readxl)
library(SuperExactTest)
library(VennDiagram)
library(DT)
library(Glimma)
load("~/Documents/RNAseq/RNAseq_S2/RNaseq_environnement.RData")

1.1 ActvsCtrl

tab_RNAseq_S2_embryo = lrt.2.tables$ActVsContr[rownames(lrt.2.tables$ActVsContr)%in%data_embryon_epiderm$SYMBOL,]
tab_RNAseq_S2_embryo$neglog10Pvalue  = -log10(tab_RNAseq_S2_embryo$PValue)
#datatable(tab_RNAseq_S2_embryo,rownames = T,filter = "top", caption = "Expression des cibles embryonnaires dans les cellules S2 ")
count_RNA = RNAseq_norm$counts[rownames(RNAseq_norm$counts)%in%rownames(tab_RNAseq_S2_embryo),]
diffGeneActContr_embryo = diffGeneActContr[rownames(diffGeneActContr)%in%rownames(tab_RNAseq_S2_embryo),]
glimmaXY(tab_RNAseq_S2_embryo$logFC, tab_RNAseq_S2_embryo$neglog10Pvalue,counts = count_RNA , status = diffGeneActContr_embryo, groups = groups,status.cols = c("red","grey","green"), main = "Gènes cibles embryonnaire dans les S2 ( ActvsCtrl)", ylab = "neglog10Pvalue", xlab = "logFC")

1.2 RepvsCtrl

tab_RNAseq_S2_embryo_rep = lrt.2.tables$RepVsContr[rownames(lrt.2.tables$RepVsContr)%in%data_embryon_epiderm$SYMBOL,]
tab_RNAseq_S2_embryo_rep$neglog10Pvalue  = -log10(tab_RNAseq_S2_embryo_rep$PValue)
#datatable(tab_RNAseq_S2_embryo_rep,rownames = T,filter = "top", caption = "Expression des cibles embryonnaires dans les cellules S2 ")
count_RNA = RNAseq_norm$counts[rownames(RNAseq_norm$counts)%in%rownames(tab_RNAseq_S2_embryo_rep),]
diffGeneRepContr_embryo = diffGeneRepContr[rownames(diffGeneRepContr)%in%rownames(tab_RNAseq_S2_embryo_rep),]
glimmaXY(tab_RNAseq_S2_embryo_rep$logFC, tab_RNAseq_S2_embryo_rep$neglog10Pvalue,counts = count_RNA , status = diffGeneRepContr_embryo, groups = groups,status.cols = c("red","grey","green"), main = "Gènes cibles embryonnaire dans les S2 (RepvsCtrl)", ylab = "neglog10Pvalue", xlab = "logFC")

1.3 ActvsRep

tab_RNAseq_S2_embryo_actrep = lrt.2.tables$ActVsRep[rownames(lrt.2.tables$ActVsRep)%in%data_embryon_epiderm$SYMBOL,]
tab_RNAseq_S2_embryo_actrep$neglog10Pvalue  = -log10(tab_RNAseq_S2_embryo_actrep$PValue)
#datatable(tab_RNAseq_S2_embryo_actrep,rownames = T,filter = "top", caption = "Expression des cibles embryonnaires dans les cellules S2 ")
count_RNA = RNAseq_norm$counts[rownames(RNAseq_norm$counts)%in%rownames(tab_RNAseq_S2_embryo_actrep),]
diffGeneActRep_embryo = diffGeneActvsRep[rownames(diffGeneActvsRep)%in%rownames(tab_RNAseq_S2_embryo_actrep),]
glimmaXY(tab_RNAseq_S2_embryo_actrep$logFC, tab_RNAseq_S2_embryo_actrep$neglog10Pvalue,counts = count_RNA , status = diffGeneActRep_embryo, groups = groups,status.cols = c("red","grey","green"), main = "Gènes cibles embryonnaire dans les S2 (ActvsRep)", ylab = "neglog10Pvalue", xlab = "logFC")

2 En les intégrant avec toutes les données S2

2.1 ActvsCtrl

tab_anno_embryonnaire_ActCtrl <- read.delim("~/Documents/RNAseq/RNAseq_S2/Comparaison_S2Embryon/tab_anno_embryonnaire_ActCtrl.txt", quote="")
tab_anno_embryonnaire_ActCtrl$neglog10Pvalue = -log10(tab_anno_embryonnaire_ActCtrl$Pvalue)



glimmaXY(tab_anno_embryonnaire_ActCtrl$logFC, tab_anno_embryonnaire_ActCtrl$neglog10Pvalue,counts = RNAseq_norm$counts , status = tab_anno_embryonnaire_ActCtrl$genesS2, groups = groups,status.cols = c("grey","grey","purple"), main = "Gènes cibles embryonnaire dans les S2 (ActvsCtrl)", ylab = "neglog10Pvalue", xlab = "logFC")

2.2 RepvsCtrl

tab_anno_embryonnaire_RepCtrl <- read.delim("~/Documents/RNAseq/RNAseq_S2/Comparaison_S2Embryon/tab_anno_embryonnaire_RepCtrl.txt", quote="")
tab_anno_embryonnaire_RepCtrl$neglog10Pvalue = -log10(tab_anno_embryonnaire_RepCtrl$Pvalue )



glimmaXY(tab_anno_embryonnaire_RepCtrl$logFC, tab_anno_embryonnaire_RepCtrl$neglog10Pvalue,counts = RNAseq_norm$counts , status = tab_anno_embryonnaire_RepCtrl$genesS2, groups = groups,status.cols = c("grey","grey","purple"), main = "Gènes cibles embryonnaire dans les S2 (RepvsCtrl)", ylab = "neglog10Pvalue", xlab = "logFC")

2.3 ActvsRep

tab_anno_embryonnaire_ActRep <- read.delim("~/Documents/RNAseq/RNAseq_S2/Comparaison_S2Embryon/tab_anno_embryonnaire_ActRep.txt", quote="")
tab_anno_embryonnaire_ActRep$neglog10Pvalue = -log10(tab_anno_embryonnaire_ActRep$Pvalue )



glimmaXY(tab_anno_embryonnaire_ActRep$logFC, tab_anno_embryonnaire_ActRep$neglog10Pvalue,counts = RNAseq_norm$counts , status = tab_anno_embryonnaire_ActRep$genesS2, groups = groups,status.cols = c("grey","grey","purple"), main = "Gènes cibles embryonnaire dans les S2 (ActvsRep)", ylab = "neglog10Pvalue", xlab = "logFC")

3 Expression des gènes cibles en S2 dans les cellules embryonnaires

tab_genesS2_dansembryon = read.table("expressiongenesciblesS2dansembryon.csv",header = T )
rownames(tab_genesS2_dansembryon)  = tab_genesS2_dansembryon$ProbeSetID
tab_genesS2_dansembryon$NegLog10Pval = -log10(tab_genesS2_dansembryon$p.value)
glimmaXY(tab_genesS2_dansembryon$logFC, -log10(tab_genesS2_dansembryon$p.value),status = tab_genesS2_dansembryon$statut,xlab = "logFC", ylab = "NegLog10Pval", anno = tab_genesS2_dansembryon, display.columns = c("gene","GeneName","logFC","NegLog10Pval"))

4 References

sessionInfo()
## R version 4.0.3 (2020-10-10)
## Platform: x86_64-apple-darwin19.6.0 (64-bit)
## Running under: macOS Big Sur 10.16
## 
## Matrix products: default
## BLAS:   /usr/local/Cellar/openblas/0.3.13/lib/libopenblasp-r0.3.13.dylib
## LAPACK: /usr/local/Cellar/r/4.0.3_2/lib/R/lib/libRlapack.dylib
## 
## Random number generation:
##  RNG:     Mersenne-Twister 
##  Normal:  Inversion 
##  Sample:  Rounding 
##  
## locale:
## [1] fr_FR.UTF-8/fr_FR.UTF-8/fr_FR.UTF-8/C/fr_FR.UTF-8/fr_FR.UTF-8
## 
## attached base packages:
## [1] grid      stats     graphics  grDevices utils     datasets  methods  
## [8] base     
## 
## other attached packages:
## [1] Glimma_2.0.0         DT_0.17              VennDiagram_1.6.20  
## [4] futile.logger_1.4.3  SuperExactTest_1.0.7 readxl_1.3.1        
## [7] drc_3.0-1            MASS_7.3-53.1       
## 
## loaded via a namespace (and not attached):
##   [1] TH.data_1.0-10              colorspace_2.0-0           
##   [3] ellipsis_0.3.1              rio_0.5.16                 
##   [5] XVector_0.30.0              GenomicRanges_1.42.0       
##   [7] ChIPpeakAnno_3.24.1         bit64_4.0.5                
##   [9] AnnotationDbi_1.52.0        fansi_0.4.2                
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##  [13] codetools_0.2-18            splines_4.0.3              
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##  [17] knitr_1.31                  jsonlite_1.7.2             
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##  [79] genefilter_1.72.1           S4Vectors_0.28.1           
##  [81] plotrix_3.8-1               GenomicFeatures_1.42.1     
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## [131] bslib_0.2.4                 askpass_1.1

Menoret, Delphine, Marc Santolini, Isabelle Fernandes, Rebecca Spokony, Jennifer Zanet, Ignacio Gonzalez, Yvan Latapie, et al. 2013. “Genome-wide analyses of Shavenbaby target genes reveals distinct features of enhancer organization.” Genome Biology 14 (8): R86. https://doi.org/10.1186/gb-2013-14-8-r86.